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Review of Scientific Instruments
Article . 2013 . Peer-reviewed
License: CC BY
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Data analysis for Seebeck coefficient measurements

Authors: de Boor, Johannes; Müller, Eckhard;

Data analysis for Seebeck coefficient measurements

Abstract

The Seebeck coefficient is one of the key quantities of thermoelectric materials and routinely measured in various laboratories. There are, however, several ways to calculate the Seebeck coefficient from the raw measurement data. We compare these different ways to extract the Seebeck coefficient, evaluate the accuracy of the results, and show methods to increase this accuracy. We furthermore point out experimental and data analysis parameters that can be used to evaluate the trustworthiness of the obtained result. The shown analysis can be used to find and minimize errors in the Seebeck coefficient measurement and therefore increase the reliability of the measured material properties.

Country
Germany
Keywords

Temperature measurement, Thermoelectric energy conversion, Data analysis, Seebeck coefficient, Contact resistance, Time measurement, Interpolation, Thermoelectric effects, Electric measurements, Thermocouples, Heaters, measurement

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
142
Top 1%
Top 10%
Top 10%
hybrid